Skip to main content
Canadian Geriatrics Journal logoLink to Canadian Geriatrics Journal
. 2018 Jun 30;21(2):157–165. doi: 10.5770/cgj.21.298

Guidelines for Gait Assessments in the Canadian Consortium on Neurodegeneration in Aging (CCNA)

Stephanie Cullen 1,*, Manuel Montero-Odasso 1,2,*,, Louis Bherer 3, Quincy Almeida 4, Sarah Fraser 5, Susan Muir-Hunter 1,6, Karen Li 7, Teresa Liu-Ambrose 8, Chris A McGibbon 9, William McIlroy 10, Laura E Middleton 10, Yanina Sarquis-Adamson 1, Olivier Beauchet 11, Bradford J McFadyen 12, José A Morais 11, Richard Camicioli 13; The Canadian Gait and Cognition Network14
PMCID: PMC6028168  PMID: 29977431

Abstract

Background

Motor and cognitive impairments are common among older adults and often co-exist, increasing their risk of dementia, falls, and fractures. Gait performance is an accepted indicator of global health and it has been proposed as a valid motor marker to detect older adults at risk of developing mobility and cognitive declines including future falls and incident dementia. Our goal was to provide a gait assessment protocol to be used for clinical and research purposes.

Methods

Based on a consensus that identified common evaluations to assess motor–cognitive interactions in community-dwelling older individuals, a protocol on how to evaluate gait in older adults for the Canadian Consortium on Neurodegeneration in Aging (CCNA) was developed.

Results

The CCNA gait assessment includes preferred and fast pace gait, and dual-task gait that comprises walking while performing three cognitively demanding tasks: counting backwards by ones, counting backwards by sevens, and naming animals. This gait protocol can be implemented using an electronic-walkway, as well as by using a regular stopwatch. The latter approach provides a simple manner to evaluate quantitative gait performance in clinics.

Conclusions

Establishing a standardized gait assessment protocol will help to assess motor–cognitive interactions in aging and neurodegeneration, to compare results across studies, and to feasibly implement and translate gait testing in clinics for detecting impending cognitive and mobility decline.

Keywords: consensus, gait, cognition, aging, neurodegenerative diseases

INTRODUCTION

As people age, they are more susceptible to mobility and cognitive impairments. These impairments often coexist early on the pathway to age-associated disability, leading to future mobility decline, falls, and dementia.(1) Epidemiological evidence on slow gait has demonstrated associations with early cognitive decline and future dementia, which draws attention to the coexistence of motor and cognitive impairments in older adults.(14)

The complex interplay between gait motor control and cognitive processes is thought to be related to common brain regions and networks shared.(1,5,6) The prevalence of motor and cognitive impairment in vulnerable populations, such as in those at risk of neurodegenerative diseases, increases with age(712) and increases the risk of future motor disability and falls.(1,1317) Gait disorders are commonly present at an early stage of dementia syndromes.(18) Deficiencies in attention, executive function, and working memory co-exist with gait abnormalities in pre-dementia states like mild cognitive impairment (MCI).(19,20) Mounting evidence shows that these motor changes start even before cognitive changes, and that a slowing of gait may precede the development of MCI by a decade.(21) Taken together, these studies suggest that there is a transition period whereby gait slowing occurs concurrently or even before cognitive loss.(16,22)

The Role of Cognition in Gait

Cognitive function plays a key role even in the regulation of routine walking, particularly in older adults.(23) Since the seminal “stops walking while talking” study(24) demonstrated that the inability to maintain a conversation while walking is a marker for future falls in older adults, observing people walking while they perform a secondary task (“dual-task paradigm”) has become an accepted way to assess motor–cognitive interaction and risk of mobility decline and falling.(1,24, 23)

In the dual-task paradigm, participants’ performance on each task alone (single-task walk, single-task cognitive) is compared to their performance during dual-task (walk and cognitive task performed simultaneously). Dual-task gait performance isolates the role of attention and executive function deficits in neural control of locomotion.(1,19,20,25) The underlying hypothesis is that two simultaneously performed tasks interfere and compete for brain cortical resources.(26,27) Therefore, dual-task gait testing can act as a “brain stress test” to detect mobility problems and risk of fall. Dual-task studies have also revealed that the cognitive demands while walking increase in the face of oligosymptomatic and covert neurologic disorders,(19,20,24,28) providing a rationale to use this “brain stress test” to detect individuals at higher risk of progression to dementia syndromes.(7)

METHODS

Integrating Gait Assessments in Aging and Cognitive Research

In 2008, our group proposed that motor and cognitive assessments should be part of the research and clinical evaluation for falls risk and mobility decline, and also for cognitive decline and dementia.(29) Since then, we have worked to advance the integration of both motor and cognitive assessments within aging research in Canada as a means to evaluate the motor–cognitive interface for the prediction of falls and cognitive decline. Our first successful attempt was in 2012 at a provincial level with the incorporation of a standardized gait and balance assessments in the cohort of the Ontario Neurodegenerative Research Initiative (ONDRI).(30) The ONDRI cohort finished recruitment in March 2017 and more than 500 older adults across the spectrum of five neurodegenerative diseases have been assessed for their gait and balance. In 2013, with the creation of the Canadian Consortium on Neurodegeneration in Aging (CCNA), we assembled the CCNA team:(12) Mobility, Exercise, and Cognition (MEC) team. We proposed a standardized and comprehensive gait assessment protocol to be used in the CCNA cohort, to investigate the interaction between mobility and cognition in neurodegenerative processes and aging across Canada. CCNA is currently recruiting a national cohort of 1,600 older adults with subjective cognitive impairments (SCI), mild cognitive impairment (MCI), vascular cognitive impairment (VCI), Alzheimer’s disease (AD), and frontotemporal dementia (FTD), with the goal of having a comprehensive medical, cognitive, and imaging assessment.

Finally, in 2015 a consensus meeting that included CCNA members specializing in mobility in aging and an international advisory board of experts (list of attendees and program available at www.gaitandbrain.com/resources/) agreed on gait measurements that would test both mobility and cognition. The resultant gait protocol is presented herein below.

RESULTS

Measurements and Procedures for the Gait Assessments (Note: A CCNA gait assessment instructional video can be found at www.gaitandbrain.com/resources/.)

Environmental Conditions

Regarding the area dedicated to gait assessment, we recommend the use of a well-lit environment with intensity-controlled artificial light to adjust for changing daylight conditions. The assessment area should be also quiet and, preferably, a closed room with no auditory or visual interference.

People to be assessed should wear comfortable and nonrestrictive clothes and wear their own footwear. Appropriate types of footwear include closed walking shoes (no slippers), with heel height not exceeding 3 cm. For follow-up gait analyses, it is highly recommended that participants use the same footwear as was worn at the baseline assessment. Depending on participants’ fall risk, we recommend safety measures be used such as a safety-belt around the participant’s waist for easy grabbing by an observer in case of an imminent fall. When using electronic walkways, it is recommended that the edges should be attached to the floor to avoid any slipping of the equipment.

Clinical Assessments

In the CCNA cohort, clinical assessments are conducted by a physician certified in geriatric medicine, neurology, psychiatry or family medicine. The clinical gait assessment includes the observation of walking to detect clinically evident gait disturbances that are being classified in the following categories: normal gait, ataxic gait, antalgic gait, cautious gait, frontal gait, hemiparetic gait, spastic gait, and shuffling gait, per CCNA cohort protocol.

Walking Testing Path

Distance over which to measure the test should be based on the characteristics of the population evaluated.(31) In older adults without mobility disability, a distance between 6 and 10 meters is needed to include at least three walking cycles to ensure that the steady-state gait velocity is measured.(16,3134)

In the proposed protocol, participants will walk a total of 8 meters, of which the middle 6 meters is recorded and timed. Gait assessments will thus be performed along a 6-meter path or using a 6-meter electronic walkway. One meter before and after the 6-meter pathway will be added in order to avoid recording acceleration and deceleration phases, as described in Figure 1. A 6-meter distance was chosen based on previous cohort studies, due to the feasibility to implement in laboratory environments, and to capture at least 12 steps in steady-state walking.

FIGURE 1.

FIGURE 1

View of the 6-meter path for gait assessments in the Canadian Consortium on Neurodegeneration in Aging; the start and end marks are outlined in red, indicating where participants should start and stop their walking to avoid recording acceleration and deceleration events

Walking times can be recorded with a stopwatch, and assessors must begin timing as the participant’s foot first crosses the start of the 6 meter path and terminate when their foot first crosses the end of the 6 meter path. When available, electronic walkways such as GAITRite® or the Zeno Walkway System® are placed in the described walking path to measure additional gait parameters during walking and dual-task walking.

Gait and Cognitive Task Assessment

The proposed gait assessment protocol is divided into three main walking conditions: 1) preferred or usual gait velocity, 2) dual-task gait at usual gait velocity, and 3) fast gait (Table 2).

TABLE 2.

Summary of gait assessments and gait variable outcomes collected in each task and used in the CCNA study

Gait Task Description Gait Variables Used as Outcomes Limitations of Task
Preferred or usual gait Participant walks at their normal speed along the path Gait velocity
Gait variability
“Slow gait” categorization (<1.0m/s)
For variability calculations a minimum of 12 steps are required
Arithmetic dual-task Participant walks while counting backwards by 1’s and then while counting backwards by 7’s out loud, starting from 100 or 150 Gait velocity
Gait variability
Number of subtractions performed
Number of mistakes
Dual-Task Cost
Arithmetic cognitive challenges are dependent on participant’s education level
Category fluency dual-task Participant walks while naming animals out loud Gait velocity
Gait variability
Number of animals named
Number of repetitions
Dual-Task Cost
Verbal cognitive challenge are dependent on verbal and semantic skills
Fast gait Participant walks as fast as they can, safely and without running Maximum capacity of gait velocity Participants may not feel comfortable walking at maximum speed; may not capture true capacity of each participant

For preferred gait velocity, participants will be instructed to walk at a comfortable and secure pace. A total of three walks are performed. If possible, we recommend that all gait trials consist of walking in the same direction. Participants with a slow gait velocity, less than 0.6m/s, or participants with lower limb disability, will be allowed to complete one walk if they are not able to perform the three trials. A minimum of approximately 12 steps is required to allow measurement of step-to-step variability during the preferred gait velocity. (35) For example, an individual who walks at 1.5 m/s would usually only have 4–5 steps per walk; therefore, we would need at least three trials of walking at preferred gait velocity. For those walking less than 1.0 m/s, two trials is commonly necessary and for those walking less than 0.5 m/s, a single walk is sufficient.

The second walking condition consists of a dual-task gait and includes three walks, each with a designated cognitively demanding task, completed at their preferred gait velocity. Commonly used and validated cognitive tasks include counting backwards by 1’s from 100 out loud, counting backwards by 7’s, and a verbal fluency task such as enumerating as many animal names as possible.(20,3638) Each of these walks will be performed once.

As part of the “Gait Pre-Assessment”, the performance in the arithmetical and verbal fluency cognitive tasks used while walking will be evaluated individually 1 hour prior to any walks for a total of 10 s each while participants are in a seated position. This will provide single-task cognitive data for comparison to the verbal output during the dual-task gait testing. The number and accuracy of the responses will be recorded. Cognitive performance will be reported as number of responses per second, calculated as (number of responses)/10. Accuracy of responses will be accounted for through the use of a corrected response rate (CRR). The CRR will be calculated as: response rate per second × percent correct.(39)

The first dual-task test administered will consist of the participant walking while simultaneously counting backward by 1’s from 100 (100-99-98…) out loud. The second dual-task test will require the participant to repeat the walk, but this time while naming animals out loud (category fluency test). In the third dual-task, the participant will be asked to walk while subtracting 7’s from 100 (100-93-86…) out loud. For subsequent assessments, it is recommended to start with a different three-digit number randomly chosen between 100 and 150. During all dual-task trials, participants are encouraged to keep walking even if the cognitive task is difficult for them (i.e., if they cannot do the subtractions or name animals). The assessor must record how many numbers were subtracted, any counting errors, or if the participant did not complete any subtractions, as well as record the number of animals listed and any animals that were repeated. These different dual-task conditions were selected based on previous research which demonstrated that subtractions depend more on working memory and attention, while naming animals out loud is more related to verbal fluency, which relies on semantic memory.(40,41)

The last walking condition is the fast gait, which is a single-task walk at a pace that is faster than the participant’s preferred gait velocity. Participants will be instructed to walk as fast as they can, as safely as they can, but without running.

Standardized Walking Instructions

We recommend the use of standardized walking instructions to explain the various tasks to participants. Details on instructions used in the CCNA cohort can be found in Table 3.

TABLE 3.

Detailed instructions for gait assessment in CCNA cohort

Walking Task Instructions
Preferred or usual gait “When I say GO, please walk at your usual pace in a comfortable and safe way until you cross this line [INDICATE END LINE].”
Counting backwards “When I say GO, please walk at your usual pace and at the same time count backwards from 100 by 1s, out loud, until you cross this line [INDICATE END LINE]. Remember that it is important that you do not stop your walking or counting.” If participant have difficulties understanding, evaluators are allowed to clarify by providing a verbal example: “For example 100, 99, 98, ... and so on”. Evaluators are allowed to prompt the tasks if participants tend to stop during the walk. If walk needs to be repeated, ask participant to start from 200 or 300.
Naming animals “When I say GO, please walk at your usual pace and at the same time try to name as many different animals as you can think of, out loud, until you cross this line [INDICATE END LINE]. Please do this out loud. Remember that it is important that you do not stop your walking or talking.”
Serial sevens “When I say GO, please walk at your usual pace and at the same time count backwards from 100 by 7s, out loud, until you cross this line [INDICATE END LINE]. Remember that it is important that you do not stop your walking even if you can’t think of the numbers.” Evaluators are allowed to prompt the tasks if participants tend to stop during the walk. If walk needs to be repeated, ask participant to start from 200 or 300.
Fast gait “When I say GO, please walk as fast as you can, as safe as you can, and without running, until you cross this line [INDICATE END LINE].”

Assistive Devices

Individuals to be tested should wear their own glasses and hearing aids. Assistive walking devices are allowed, if needed. We recommend first asking the participant if they are comfortable performing one trial without the assistive walking device, to assess if the participant is able to walk without assistance. If they are able to do this, then all trials should be done without the device and an additional member of the research team should shadow the participant as they walk down the electronic walkway in case the participant loses balance. If the person is uncomfortable without the device or if they cannot safely ambulate without it, the device should be used for all trials. If devices are used during gait testing, the type of device (e.g., cane, walker) should be recorded and it should be noted that the device was used for all trials. (Gait Cost of Using a Mobility Aid in Older Adults with Alzheimer’s Disease. Muir-Hunter SW, Montero-Odasso M. J Am Geriatr Soc. 2016 Feb;64(2):437–8. doi: 10.1111/jgs.13973.)

The attentional demands of ambulating with an assistive device in older adults with Alzheimer’s disease. Muir-Hunter SW, Montero-Odasso M. Gait Posture. 2017 May;54:202–208. doi: 10.1016/j.gaitpost.2017.03.011. Epub 2017 Mar 10

Prioritization

Instructions for prioritization of tasks while dual-task testing will depend on the main research question or if gait is evaluated in a clinical encounter. For the purposes of the CCNA cohorts, participants will be instructed to pay equal attention to both gait and the cognitive task; if a participant stops either task during the trial, they will be prompted to resume. Providing no instruction to prioritize gait over cognitive task or vice-versa allows both gait and cognitive task to vary and has previously been shown to provide a better representation of what happens naturally.(42, 27) On the other hand, if the effect of cognitive load on gait is the main question, the participants should be instructed to prioritize the cognitive task over walking, in order to see the outcome that this has on their gait.(42) In clinics, allowing both gait and cognitive tasks to vary, without giving clear prioritization instructions, provides a better representation of mobility performance while doing daily living activities.

Rationale for the Minimum Set of Variables to be Analyzed in the CCNA Cohort

Gait Velocity

Gait velocity provides important information on the risk of future adverse events, as a slowing in gait velocity has been associated with future falls, hospitalizations, disability, cognitive impairment, progression to dementia, and mortality.(33,4345) It can be measured, as described above, in the preferred gait velocity condition, dual-task condition and fast gait condition. Fast gait velocity has been proposed to be an indicator of gait velocity reserve and predict disability, and thus we have incorporated this modality in our protocols.(46) Finally, we also analyze dual-task velocities as overall measures of the motor-cognitive interaction.

Spatiotemporal Quantitative Gait Variables

When electronic walkways are available, we recommend measuring six gait variables that have previously been shown to be sensitive to cognitive changes and associated with future cognitive and mobility decline.(5,47,48) Besides gait velocity as described above, these variables are cadence (steps/min), stride time (milliseconds), stride length (cm), step width (cm), and double support time (milliseconds) (Table 4).

TABLE 4.

Definitions of quantitative spatiotemporal gait variables analysed in CCNA cohort

Variable Units Definition
Velocity meters/second Distance covered by the time to ambulate
Cadence steps/minute Number of steps by the time to ambulate
Stride length meters Distance between heel points of two consecutive footfalls of the same foot
Step length meters Anterioposterior distance between the heel points of two consecutive footfalls of the opposite foot
Step width meters Mediolateral distance between the heel points of two consecutive footfalls of the opposite foot
Stride time seconds Duration to ambulate one stride length
Step time seconds Duration to ambulate one step length
Double support time seconds Duration of when both limbs are in contact with the ground

Gait Variability

A sensitive measure of dynamic stability during walking is gait variability, defined as the stride-to-stride variation in time or distance of the quantitative variables listed above.(49) This measure quantifies the temporal automaticity of gait, with greater variability indicating reduced consistency and a more unstable gait pattern. Evaluating gait variability is an accurate methodology to identify subtle changes in walking due to pathological conditions or disease. For instance, cognitively normal older adults have low gait variability; however, high gait variability has been described in Parkinson’s disease and Alzheimer’s disease, and has been associated with high risk of future falls and mobility decline.(47,48,5052) Gait variability may serve as a clinically relevant parameter in the evaluation of mobility and as a responsive measure for different interventions in fall prevention.(53)

Dual-Task Gait Cost

The dual-task gait cost (DTGC) provides a measure of the mobility “cost” that an individual incurs when walking and performing a simultaneous cognitive task, compared to only walking. This DTGC can be assessed using the following formula: DTGC = [(usual gait - dual-task gait) / usual gait] × 100. DTGC can be calculated using usual and dual-task values from any of the six quantitative variables listed above, as well as for variability. Dual-task gait cost has been demonstrated to correlate with the measures of cognitive ability (i.e., low cognitive performance is associated with high DTGC), and helps to detect older adult at risk of future mobility and cognitive decline, including progression to dementia.(7,36,5456)

Dual-Task Cognitive Cost

The dual-task cognitive cost (DTCC) provides a measure of the effect of the walking task over cognitive performance. Commonly, older adults prioritize gait (motor performance) over cognitive performance to maintain the posture first strategy.(57) As such, DTCC may be larger than DTGC, but would be missing information without the calculation of costs in both domains. The formula to calculate the DTCC is: DTCC = [(Single-task cognition - dual-task cognition) / Single-task cognition] × 100, if the dependent measure is accuracy or number of items completed. However, if reaction times are measured, the subtraction would be reversed (Dual-task cognition - Single-task cognition) to indicate the slow-down relative to the denominator, Single-task cognition.

DISCUSSION

This is the first pan-Canadian protocol guideline to standardize gait assessments as a means to assess the motor–cognitive interaction. A common protocol for gait assessment will provide a wealth of data that can be compared across many research sites in Canada, helping to increase the applicability of gait testing in both research and clinical settings. The gait assessment protocol described here is used in the ONDRI cohort, the CCNA cohort, and in the Gait and Brain Study, thus potentially reaching more than 2,500 older research participants across Canada in these three different longitudinal studies.(7,30) The prospective assessment of quantitative gait performance under preferred and fast velocity, and dual-task conditions in the targeted neurodegenerative diseases included in the CCNA cohort will expand our understanding about the relationships between gait and cognition which, in turn, will help to identify modifiable factors or mechanisms to prevent falls in older adults with and without neurodegenerative conditions, and to detect older individuals at higher risk of cognitive decline and dementia incidence.

More importantly, our protocol can be applied using a simple stopwatch and having a known distance, like a corridor, which facilitates its clinical applicability in non-research settings. Given the growing recognition of the importance of gait as a mobility marker of overall health and function in aging and disease, establishing a common gait assessment protocol will assist in the development of standardized mobility assessments, and allow for comparisons across disease states. While gait may well serve as the sixth vital sign(33,34,58,59) and a motor biomarker for neurodegenerative diseases,(60) a standard approach used to assess gait and the cognitive-motor interface (e.g., dual-tasking) in research and clinical settings is critically important to advance its use in routine clinical care.

The protocol is also compatible with other portable measurement systems besides instrumented walkways. For example, accelerometer-based wearable sensors can be utilized to quantify common clinical parameters of gait, including gait speed and step-to-step variability.(61) Although relatively new in the clinical setting, these inexpensive and highly portable technologies have been proven reliable and valid in a controlled setting, and are showing great promise for separating the effects of mobility and cognitive impairments on gait function.(62)

Finally, the guidelines presented here are intended to facilitate collaborations across groups and networks in research in aging and to also provide guidance to clinicians who wish to implement quantitative and spatiotemporal gait analysis in clinical settings.

TABLE 1.

Canadian Gait and Cognition Network institutions and members

Canadian Gait and Cognition Network

Province City Institution Member
Ontario London Gait and Brain Lab, Schulich School of Medicine & Dentistry. University of Western Ontario Manuel Montero-Odasso
Schulich School of Medicine & Dentistry. University of Western Ontario Robert Bartha
Schulich School of Medicine & Dentistry. University of Western Ontario Michael Borrie
Regional Mental Health Care-London. University of Western Ontario Amer Burhan
Schulich School of Medicine & Dentistry. University of Western Ontario Vladimir Hachinski
School of Physical Therapy. University of Western Ontario Susan Muir-Hunter
School of Kinesiology. University of Western Ontario Kevin Shoemaker
Epidemiology and Biostatistics. University of Western Ontario Mark Speechley
Schulich School of Medicine & Dentistry. University of Western Ontario Luciano Sposato
Pharmacy department. St Joseph’s Health Care Leanne Vanderhaeghe
Department of Psychiatry. University of Western Ontario Akshya Vasudev

Ottawa Faculty of Health Sciences, Interdisciplinary School of Health Sciences. University of Ottawa Sarah Fraser

Waterloo The Sun Life Financial Movement Disorders Research and Rehabilitation Centre. Wilfrid Laurier University Quincy Almeida
Faculty of Applied Health Sciences, Department of Kinesiology. University of Waterloo William McIlroy
Faculty of Applied Health Sciences, Department of Kinesiology. University of Waterloo Laura Middleton

Québec Montréal Department of Medicine, University of Montreal, Montreal Heart Institute and Institut universitaire de gériatrie de Montréal Louis Bherer
Division of Geriatric Medicine. McGill University / Université McGill Olivier Beauchet
McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University. Julien Doyon
Department of Psychology. Concordia University Karen Li
Division of Geriatric Medicine. McGill University / Université McGill José Morais

Quebec City Department of Rehabilitation. Université Laval Bradford McFadyen

Alberta Edmonton Glenrose Rehabilitation Hospital. University of Alberta Richard Camicioli

British Columbia Vancouver Aging, Mobility, and Cognitive Neuroscience Lab, Department of Physical Therapy. University of British Columbia Teresa Liu-Ambrose

New Brunswick Fredericton Faculty of Kinesiology and Institute of Biomedical Engineering. University of New Brunswick Chris A. McGibbon

Pennsylvania Pittsburgh Department of Biomedical Informatics. University of Pittsburgh Ervin Sejdic

ACKNOWLEDGEMENTS

This study is funded by Canadian Consortium on Neurodegeneration in Aging (CCNA – Grant# “FRN” CNA 137794) which receives funding from the Canadian Institutes of Health Research and other partner organizations. S. Cullen is a Master’s candidate in Kinesiology under Dr. Montero-Odasso’s supervision and funded by the Gait and Brain Lab, Parkwood Institute, University of Western Ontario and Lawson Health Research Institute through the Early Research Award of Ontario.

Footnotes

CONFLICT OF INTEREST DISCLOSURES

The authors declare that no conflicts of interest exist.

REFERENCES

  • 1.Montero-Odasso M, Verghese J, Beauchet O, et al. Gait and cognition: a complementary approach to understanding brain function and the risk of falling. J Am Geriatr Soc. 2012;60(11):2127–36. doi: 10.1111/j.1532-5415.2012.04209.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Boyle PA, Buchman AS, Wilson RS, et al. Association of muscle strength with the risk of Alzheimer disease and the rate of cognitive decline in community-dwelling older persons. Arch Neurol. 2009;66(11):1339–44. doi: 10.1001/archneurol.2009.240. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Fitzpatrick AL, Buchanan CK, Nahin RL, et al. Associations of gait speed and other measures of physical function with cognition in a healthy cohort of elderly persons. J Gerontol A Biol Sci Med Sci. 2007;62(11):1244–51. doi: 10.1093/gerona/62.11.1244. [DOI] [PubMed] [Google Scholar]
  • 4.Soumaré A, Tavernier B, Alpérovitch A, et al. A cross-sectional and longitudinal study of the relationship between walking speed and cognitive function in community-dwelling elderly people. J Gerontol A Biol Sci Med Sci. 2009;64(10):1058–65. doi: 10.1093/gerona/glp077. [DOI] [PubMed] [Google Scholar]
  • 5.Montero-Odasso M, Oteng-Amoako A, Speechley M, et al. The motor signature of mild cognitive impairment: results from the gait and brain study. J Gerontol A Biol Sci Med Sci. 2014;69(11):1415–21. doi: 10.1093/gerona/glu155. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Rosso AL, Studenski SA, Chen WG, et al. Aging, the central nervous system, and mobility. J Gerontol A Biol Sci Med Sci. 2013;68(11):1379–86. doi: 10.1093/gerona/glt089. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Montero-Odasso MM, Sarquis-Adamson Y, Speechley M, et al. Association of dual-task gait with incident dementia in mild cognitive impairment: results from the Gait and Brain Study. JAMA Neurol. 2017;74(7):857–65. doi: 10.1001/jamaneurol.2017.0643. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Annweiler C, Beauchet O, Celle S, et al. Contribution of brain imaging to the understanding of gait disorders in Alzheimer’s disease: a systematic review. Am J Alzheimers Dis Other Demen. 2012;27(6):371–80. doi: 10.1177/1533317512454710. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Annweiler C, Beauchet O, Bartha R, et al. Motor cortex and gait in mild cognitive impairment: a magnetic resonance spectroscopy and volumetric imaging study. Brain. 2013;136(3):859–71. doi: 10.1093/brain/aws373. [DOI] [PubMed] [Google Scholar]
  • 10.Annweiler C, Beauchet O, Bartha R, et al. Slow gait in MCI is associated with ventricular enlargement: results from the Gait and Brain Study. J Neural Transm. 2013;120(7):1083–92. doi: 10.1007/s00702-012-0926-4. [DOI] [PubMed] [Google Scholar]
  • 11.Annweiler C, Beauchet O, Bartha R, et al. Vitamin D and caudal primary motor cortex: a magnetic resonance spectroscopy study. PLoS One. 2014;9:e87314. doi: 10.1371/journal.pone.0087314. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Annweiler C, Montero-Odasso M, Bartha R, et al. Association between gait variability and brain ventricle attributes: a brain mapping study. Exp Gerontol. 2014;57:256–63. doi: 10.1016/j.exger.2014.06.015. [DOI] [PubMed] [Google Scholar]
  • 13.Camicioli R, Howieson D, Oken B, et al. Motor slowing precedes cognitive impairment in the oldest old. Neurology. 1998;50(5):1496–98. doi: 10.1212/WNL.50.5.1496. [DOI] [PubMed] [Google Scholar]
  • 14.Camicioli R, Majumdar SR. Relationship between mild cognitive impairment and falls in older people with and without Parkinson’s disease: 1-year prospective cohort study. Gait Posture. 2010;32(1):87–91. doi: 10.1016/j.gaitpost.2010.03.013. [DOI] [PubMed] [Google Scholar]
  • 15.Liu-Ambrose TY, Ashe MC, Graf P, et al. Increased risk of falling in older community-dwelling women with mild cognitive impairment. Phys Ther. 2008;88(12):1482–91. doi: 10.2522/ptj.20080117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Montero-Odasso M, Schapira M, Varela C, et al. Gait velocity in senior people. An easy test for detecting mobility impairment in community elderly. J Nutr Health Aging. 2004;8(5):340–43. [PubMed] [Google Scholar]
  • 17.Montero-Odasso M, Beland F, Fletcher J, et al. Mobility profile as a predictor of adverse events in community frail elderly [abstract] J Am Geriatr Soc. 2005;53:S81. [Google Scholar]
  • 18.Verghese J, LeValley A, Hall CB, et al. Epidemiology of gait disorders in community-residing older adults. J Am Geriatr Soc. 2006;54(2):255–61. doi: 10.1111/j.1532-5415.2005.00580.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Montero-Odasso M, Bergman H, Phillips NA, et al. Dual-tasking and gait in people with mild cognitive impairment. The effect of working memory. BMC Geriatr. 2009;9:41. doi: 10.1186/1471-2318-9-41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Montero-Odasso M, Muir SW, Speechley M. Dual-task complexity affects gait in people with mild cognitive impairment: the interplay between gait variability, dual tasking, and risk of falls. Arch Phys Med Rehabil. 2012;93(2):293–99. doi: 10.1016/j.apmr.2011.08.026. [DOI] [PubMed] [Google Scholar]
  • 21.Buracchio T, Dodge HH, Howieson D, et al. The trajectory of gait speed preceding mild cognitive impairment. Arch Neurol. 2010;67(8):980–86. doi: 10.1001/archneurol.2010.159. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Kueper JK, Speechley M, Lingum NR, et al. Motor function and incident dementia: a systematic review and meta-analysis. Age Ageing. 2017;46(5):729–38. doi: 10.1093/ageing/afx084. [DOI] [PubMed] [Google Scholar]
  • 23.Hausdorff JM, Yogev G, Springer S, et al. Walking is more like catching than tapping: gait in the elderly as a complex cognitive task. Exp Brain Res. 2005;164(4):541–48. doi: 10.1007/s00221-005-2280-3. [DOI] [PubMed] [Google Scholar]
  • 24.Lundin-Olsson L, Nyberg L, Gustafson Y. “Stops walking when talking” as a predictor of falls in elderly people. Lancet. 1997;349(9052):617. doi: 10.1016/S0140-6736(97)24009-2. [DOI] [PubMed] [Google Scholar]
  • 25.Woollacott M, Shumway-Cook A. Attention and the control of posture and gait: a review of an emerging area of research. Gait Posture. 2002;16(1):1–14. doi: 10.1016/S0966-6362(01)00156-4. [DOI] [PubMed] [Google Scholar]
  • 26.Yogev-Seligmann G, Hausdorff JM, Giladi N. The role of executive function and attention in gait. Mov Disord. 2008;23(3):329–42. doi: 10.1002/mds.21720. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Fraser S, Bherer L. Age-related decline in divided-attention: from theoretical lab research to practical real-life situations. Wiley Interdiscip Rev Cogn Sci. 2013;4(6):623–40. doi: 10.1002/wcs.1252. [DOI] [PubMed] [Google Scholar]
  • 28.Muir SW, Speechley M, Wells J, et al. Gait assessment in mild cognitive impairment and Alzheimer’s disease: the effect of dual-task challenges across the cognitive spectrum. Gait Posture. 2012;35(1):96–100. doi: 10.1016/j.gaitpost.2011.08.014. [DOI] [PubMed] [Google Scholar]
  • 29.Montero-Odasso M, Bherer L, Studenski S, et al. Mobility and Cognition in Seniors. Report from the 2008 Institute of Aging CIHR Mobility and Cognition Workshop. Can Geriatr J. 2015;18(3):159–67. doi: 10.5770/cgj.18.188. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Montero-Odasso M, Pieruccini-Faria F, Bartha R, et al. Motor phenotype in neurodegenerative disorders: gait and balance platform study design protocol for the Ontario Neurodegenerative Research Initiative (ONDRI) J Alzheimers Dis. 2017;59(2):707–21. doi: 10.3233/JAD-170149. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Berg K, Norman KE. Functional assessment of balance and gait. Clin Geriatr Med. 1996;12(4):705–23. [PubMed] [Google Scholar]
  • 32.Bendall MJ, Bassey EJ, Pearson MB. Factors affecting walking speed of elderly people. Age Ageing. 1989;18(5):327–32. doi: 10.1093/ageing/18.5.327. [DOI] [PubMed] [Google Scholar]
  • 33.Montero-Odasso M, Schapira M, Soriano ER, et al. Gait velocity as a single predictor of adverse events in healthy seniors aged 75 years and older. J Gerontol A Biol Sci Med Sci. 2005;60(10):1304–09. doi: 10.1093/gerona/60.10.1304. [DOI] [PubMed] [Google Scholar]
  • 34.Montero-Odasso M. The value of gait velocity test for high-function populations. J Am Geriatr Soc. 2006;54(12):1949–50. doi: 10.1111/j.1532-5415.2006.00952.x. [DOI] [PubMed] [Google Scholar]
  • 35.Lord S, Howe T, Greenland J, et al. Gait variability in older adults: a structured review of testing protocol and clinimetric properties. Gait Posture. 2011;34(4):443–50. doi: 10.1016/j.gaitpost.2011.07.010. [DOI] [PubMed] [Google Scholar]
  • 36.Hausdorff JM, Schweiger A, Herman T, et al. Dual-task decrements in gait: contributing factors among healthy older adults. J Gerontol A Biol Sci Med Sci. 2008;63(12):1335–43. doi: 10.1093/gerona/63.12.1335. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Montero-Odasso M, Casas A, Hansen KT, et al. Quantitative gait analysis under dual-task in older people with mild cognitive impairment: a reliability study. J Neuroeng Rehabil. 2009;6:35. doi: 10.1186/1743-0003-6-35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Yogev G, Giladi N, Peretz C, et al. Dual tasking, gait rhythmicity, and Parkinson’s disease: which aspects of gait are attention demanding? Eur J Neurosci. 2005;22(5):1248–56. doi: 10.1111/j.1460-9568.2005.04298.x. [DOI] [PubMed] [Google Scholar]
  • 39.Hall CD, Echt KV, Wolf SL, et al. Cognitive and motor mechanisms underlying older adults’ ability to divide attention while walking. Phys Ther. 2011;91(7):1039–50. doi: 10.2522/ptj.20100114. [DOI] [PubMed] [Google Scholar]
  • 40.Hittmair-Delazer M, Semenza C, Denes G. Concepts and facts in calculation. Brain. 1994;117(4):715–28. doi: 10.1093/brain/117.4.715. [DOI] [PubMed] [Google Scholar]
  • 41.Weiss EM, Siedentopf C, Hofer A, et al. Brain activation pattern during a verbal fluency test in healthy male and female volunteers: a functional magnetic resonance imaging study. Neurosci Lett. 2003;352(3):191–94. doi: 10.1016/j.neulet.2003.08.071. [DOI] [PubMed] [Google Scholar]
  • 42.Verghese J, Kuslansky G, Holtzer R, et al. Walking while talking: effect of task prioritization in the elderly. Arch Phys Med Rehabil. 2007;88(1):50–53. doi: 10.1016/j.apmr.2006.10.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Studenski S, Perera S, Patel K, et al. Gait speed and survival in older adults. JAMA. 2011;305:50–58. doi: 10.1001/jama.2010.1923. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Waite LM, Grayson DA, Piguet O, et al. Gait slowing as a predictor of incident dementia: 6-year longitudinal data from the Sydney Older Persons Study. J Neurol Sci. 2005;229–230:89–93. doi: 10.1016/j.jns.2004.11.009. [DOI] [PubMed] [Google Scholar]
  • 45.Perera S, Patel KV, Rosano C, et al. Gait speed predicts incident disability: a pooled analysis. J Gerontol A Biol Sci Med Sci. 2016;71(1):63–71. doi: 10.1093/gerona/glv126. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Artaud F, Singh-Manoux A, Dugravot A, et al. Decline in fast gait speed as a predictor of disability in older adults. J Am Geriatr Soc. 2015;63(6):1129–36. doi: 10.1111/jgs.13442. [DOI] [PubMed] [Google Scholar]
  • 47.Verghese J, Wang C, Lipton RB, et al. Quantitative gait dysfunction and risk of cognitive decline and dementia. J Neurol Neurosurg Psychiatry. 2007;78(9):929–35. doi: 10.1136/jnnp.2006.106914. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Verghese J, Annweiler C, Ayers E, et al. Motoric cognitive risk syndrome: multicountry prevalence and dementia risk. Neurology. 2014;83(8):718–26. doi: 10.1212/WNL.0000000000000717. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Hausdorff JM. Gait variability: methods, modeling and meaning. J Neuroeng Rehabil. 2005;2:19. doi: 10.1186/1743-0003-2-19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Herman T, Giladi N, Gurevich T, et al. Gait instability and fractal dynamics of older adults with a “cautious” gait: why do certain older adults walk fearfully? Gait Posture. 2005;21(2):178–85. doi: 10.1016/j.gaitpost.2004.01.014. [DOI] [PubMed] [Google Scholar]
  • 51.Brach JS, Studenski SA, Perera S, et al. Gait variability and the risk of incident mobility disability in community-dwelling older adults. J Gerontol A Biol Sci Med Sci. 2007;62(9):983–88. doi: 10.1093/gerona/62.9.983. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Hausdorff JM, Rios DA, Edelberg HK. Gait variability and fall risk in community-living older adults: a 1-year prospective study. Arch Phys Med Rehabil. 2001;82(8):1050–56. doi: 10.1053/apmr.2001.24893. [DOI] [PubMed] [Google Scholar]
  • 53.Paleacu D, Shutzman A, Giladi N, et al. Effects of pharmacological therapy on gait and cognitive function in depressed patients. Clin Neuropharmacol. 2007;30(2):63–71. doi: 10.1097/01.wnf.0000240949.41691.95. [DOI] [PubMed] [Google Scholar]
  • 54.Allali G, Kressig RW, Assal F, et al. Changes in gait while backward counting in demented older adults with frontal lobe dysfunction. Gait Posture. 2007;26(4):572–76. doi: 10.1016/j.gaitpost.2006.12.011. [DOI] [PubMed] [Google Scholar]
  • 55.Camicioli R, Howieson D, Lehman S, et al. Talking while walking: the effect of a dual task in aging and Alzheimer’s disease. Neurology. 1997;48(4):955–58. doi: 10.1212/WNL.48.4.955. [DOI] [PubMed] [Google Scholar]
  • 56.Camicioli R, Bouchard T, Licis L. Dual-tasks and walking fast: relationship to extra-pyramidal signs in advanced Alzheimer disease. J Neurol Sci. 2006;248(1–2):205–09. doi: 10.1016/j.jns.2006.05.013. [DOI] [PubMed] [Google Scholar]
  • 57.Li KZ, Lindenberger U, Freund AM, et al. Walking while memorizing: age-related differences in compensatory behavior. Psychol Sci. 2001;12(3):230–37. doi: 10.1111/1467-9280.00341. [DOI] [PubMed] [Google Scholar]
  • 58.Fritz S, Lusardi M. White paper: “Walking speed: the sixth vital sign”. J Geriatr Phys Ther. 2009;32(2):2–5. doi: 10.1519/00139143-200932020-00002. [DOI] [PubMed] [Google Scholar]
  • 59.Middleton A, Fritz SL, Lusardi M. Walking speed: the functional vital sign. J Aging Phys Act. 2015;23(2):314–22. doi: 10.1123/japa.2013-0236. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Montero-Odasso M. Gait as a biomarker of cognitive impairment and dementia syndromes. Quo vadis? [editorial] Eur J Neurol. 2016;23(3):437–38. doi: 10.1111/ene.12908. [DOI] [PubMed] [Google Scholar]
  • 61.Beyea J, McGibbon CA, Sexton A, et al. Convergent validity of a wearable sensor system for measuring sub-task performance during the timed Up-and-Go Test. Sensors. 2017;17(4):934. doi: 10.3390/s17040934. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Howcroft J, Kofman J, Lemaire ED, et al. Analysis of dual-task elderly gait in fallers and non-fallers using wearable sensors. J Biomech. 2016;49(7):992–1001. doi: 10.1016/j.jbiomech.2016.01.015. [DOI] [PubMed] [Google Scholar]

Articles from Canadian Geriatrics Journal are provided here courtesy of Canadian Geriatrics Society

RESOURCES